An end-to-end machine learning project that predicts automotive parts shortages for a major automotive manufacturing and distribution company. This project showcases data preprocessing, exploratory analysis, feature engineering, and robust predictive modeling (including XGBoost) to drive actionable insights under a strict NDA.

Exploratory Data Analysis for Audio Data

This repository contains my work on Oasis Info byte’s data analytics one month internship program.

Proyek Submision Dicoding Indonesia - Belajar Analisis Data dengan Python

Culled from the UCI Machine Learning Repository, the Dry Bean Dataset (licensed under CC BY 4.0) provides valuable insights into bean classification and is a valuable resource for machine learning enthusiasts.

We leverage machine learning and data analysis to address real-world challenges in the copper industry. Our documentation encompasses data preprocessing, feature engineering, classification, regression, and model selection. Explore how we've enhanced predictive capabilities to optimize manufacturing solutions.

Combining climate data (air pollution, temperature, precipitation, etc.) and social media/consumer behavior data to examine the relationship between people’s perception of climate change and air quality in specific regions (e.g. states in the US) and predict possible future trends.

We use machine learning and data analysis to predict resale prices of Singapore flats. Our documentation covers data preprocessing, feature engineering, regression, and model selection. Discover how we improved predictions to optimize solutions.

EDA Analysis of ECG Signals to Detect Arrhythmia

This project helps user to perform trend analysis, pattern recognition, and deriving data insights through exploratory data analysis (EDA) for the Airbnb data. Created an interactive Powerbi dashboard to analyze Airbnb data.